Overview of structural reliability methods

Vrouwenvelder, Ton; Karadeniz, H.

doi:10.1201/b10572-20

Cited by 5 publications

(9 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The methods that calculate the POF directly from this integration are known as Level III reliability methods, which are perceived to be most accurate. The most common relevant level III methods are: (1) Monte Carlo Methods (MC), (2) NI, (3) Analytical Integration (AI), (4) Surrogate Models (SMs), and (5) Stochastic Finite Element Method (SFEM) [1,8,9]. Theoretical background on AI, NI, and MCS can be found in [30].…”

Section: Level III (Direct) Reliability Methodsmentioning

confidence: 99%

“…The error expression is minimized with respect to the vector a to calculate the unknown coefficients. After determining a response surface failure function from Equation (10), a standard reliability technique is used to compute the POF [8,9].…”

Section: Response Surface Methodsmentioning

confidence: 99%

“…Several computational techniques may be employed for the RA with implicit failure functions. The major techniques include Perturbation Techniques, Neumann expansion solution, RS approach, and branch and bound techniques [8,9]. A state-of-the-art review on SFEM is presented in [80].…”

Section: Stochastic Finite Element Methods (Sfem)mentioning

confidence: 99%

“…The perturbation techniques are desirable owing to their efficiency in computation times and accuracy. Theoretical background on perturbation method can be found in [8,9]. Li et al [81] proposed a new class of hybrid perturbation-Galerkin methods to establish the response function (surface) to overcome the major challenge in the RA of the complex structure of being unable to find the response function from which the LS can be determined.…”

Section: Stochastic Finite Element Methods (Sfem)mentioning

confidence: 99%

“…Structural reliability (SR) can be defined as 'the ability that a structure complies with given requirements under specific conditions during its intended design life' [4][5][6][7]. Suitable SR levels will, therefore, avoid intolerable damage to a structure over a specified period of time [8,9]. Use of probabilistic methods in structural design is increasing, and many standards have made allowance for reliability analysis (RA) either in the calibration of partial safety factors or in design and analysis [10].…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

A Systematic Review of Structural Reliability Methods for Deformation and Fatigue Analysis of Offshore Jacket Structures

Shittu

Kolios

Mehmanparast

2020

Metals

View full text Add to dashboard Cite

This paper presents the state of the art in Structural Reliability Analysis (SRA) methods with a view of identifying key applications of each method and its proposed variations, qualifying characteristics, advantages, and limitations. Due to the increasing complexity and scale of modern offshore jacket structures, it becomes increasingly necessary to propose an accurate and efficient approach for the assessment of uncertainties in their material properties, geometric dimensions, and operating environments. SRA, as a form of uncertainty analysis, has been demonstrated to be a useful tool in the design of structures because it can directly quantify how uncertainty about input parameters can affect structural performance. Herein, attention was focused specifically on the probabilistic fracture mechanics approach because this accounts accurately for fatigue reliability mostly encountered as being dominant in the design of such structures. The well-established analytical/approximate methods such as the First- and Second-Order Reliability Methods (FORM/SORM) are widely used as they offer a good balance between accuracy and efficiency for realistic problems. They are, however, inaccurate in cases of highly non-linear systems. As a result, they have been modified using methods such as conjugate search direction approach, saddle point approximation, subset simulation, evidence theory, etc. in order to improve accuracy. Initially, direct simulations methods such as the Monte Carlo Simulation Method (MCS) with its various variance reduction techniques such as the Importance Sampling (IS), Latin Hypercube Sampling (LHS), etc. are ideal for structures having non-linear limit states but perform poorly for problems that calculate very low probabilities of failure. Overall, each method has its own merits and limitation, with FORM/SORM being the most commonly used, but recently, simulation methods have increasingly been used due to continuous advances in computation powers. Other relevant methods include the Response Surface Methods (RSM) and the Surrogate Models/Meta-models (SM/MM), which are advanced approximation methods and are ideal for structures with implicit limit state functions and high-reliability indices. Combinations of advanced approximation methods and reliability analysis methods are also found in literature as they can be suitable for complex, highly non-linear problems.

show abstract

Section: Level III (Direct) Reliability Methodsmentioning

confidence: 99%

Section: Response Surface Methodsmentioning

confidence: 99%